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The conventional process of last-mile delivery logistics often leads to safety problems for road users and a high level of environmental pollution. Delivery drivers must deal with frequent stops, search for a convenient parking spot and sometimes navigate through the narrow streets causing traffic congestion and possibly safety issues for the ego vehicle as well as for other traffic participants. This process is not only time consuming but also environmentally impactful, especially in low-emission zones where prolonged vehicle idling can lead to air pollution and to high operational costs. To overcome these challenges, a reliable system is required that not only ensures the flexible, safe and smooth delivery of goods but also cuts the costs and meets the delivery target.

The optimization and further development of automated driving functions offers great potential to relieve the driver in various driving situations and increase road safety. Simulative testing in particular is an indispensable tool in this process, allowing conclusions to be drawn about the design of automated driving functions at a very early stage of development. In this context, the use of driving simulators provides support so that the driving functions of tomorrow can be experienced in a very safe and reproducible environment. The focus of the acceptance and optimization of automated driving functions is particularly on vehicle lateral control functions. As part of this paper, a test person study was carried out regarding manual vehicle lateral control on the dynamic vehicle road simulator at the Institute of Automotive Engineering.

With the automotive industry's increasing focus on electromobility and the growing share of electric cars, new challenges are arising for the development of electric motors. The requirements for torque and power of traction motors are constantly growing, while installation space, costs and weight are increasingly becoming limiting factors. Moreover, there is an inherent conflict in the design between power density and efficiency of an electric motor. Thus, a main focus in today's development lies on space-saving and yet effective and innovative cooling systems. This paper presents an approach for a multi-physical optimization that combines the domains of electromagnetics and thermodynamics. Based on a reference machine, this simulative study examins a total of nine different stator cooling concepts varying the cooling duct positions and end-winding cooling concepts.

The courier express parcel service industry (CEP industry) has experienced significant changes in the recent years due to increasing parcel volume. At the same time, the electrification of the vehicle fleets poses additional challenges. A major advantage of battery electric CEP vehicles compared to internal combustion engine vehicles is the ability to regenerate the kinetic energy of the vehicle in the frequent deceleration phases during parcel delivery. If the battery is cold the maximum recuperation power of the powertrain is limited by a reduced chemical reaction rate inside the battery. In general, the maximum charging power of the battery depends on the state of charge and the battery temperature. Due to the low power demand for driving during CEP operation, the battery self-heating is comparably low under cold ambient conditions. Without active conditioning of the battery, potential regenerative energy is lost as a result of the cold battery.

In recent years, the urgent need to fully exploit the fuel economy potential of the Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) have led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure, in which an agent is able to learn the optimal control strategy through the feedback received by a direct interaction with the environment. Therefore, in this study, a new Soft Actor-Critic agent (SAC), which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability.

Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

Expansion chamber mufflers are commonly applied to reduce noise in HVAC. Dissipative materials, such as microperforated plates (MPPs), are often applied to achieve a more broadband mitigation effect. Such mufflers are typically characterized in the frequency domain, assuming time-harmonic excitation. From a computational point of view, transient analyses are more challenging. A transformation of the equivalent fluid model or impedance boundary conditions into the time domain induces convolution integrals. We apply the recently proposed finite element formulation of a time domain equivalent fluid (TDEF) model to simulate the transient response of dissipative acoustic media to arbitrary unsteady excitation. As most time domain approaches, the formulation relies on approximating the frequency-dependent equivalent fluid parameters by a sum of rational functions composed of real-valued or complex-conjugated poles.

Dampers (PDs) are passive devices employed in vibration and noise control applications. They consist of a cavity filled with particles that, when fixed to a vibrating structure, dissipate vibrational energy through friction and collisions among the particles. These devices have been extensively documented in the literature and find widespread use in reducing vibrations in structural machinery components subjected to significant dynamic loads during operation. However, their application in reducing vehicle interior sound has received, up to now, relatively little attention. Previous work by the authors has proven the effectiveness of particle dampers in mitigating vibrations in vehicle body panels, achieving a notable reduction in structure-borne noise within the vehicle cabin with an additional weight comparable to or even lower than that of bituminous damping treatments traditionally used for this purpose.

The current work presents the results of an investigation on the impact of renewable fuels on the combustion and emissions of a turbocharged compression-ignition internal combustion engine. An experimental study was undertaken and the engine settings were not modified to account for the fuel's chemical and physical properties, to analyze the performance of the fuel as a potential drop-in alternative fuel. Three fuels were tested: mineral diesel, a blend of it with waste cooking oil biodiesel and a hydrogenated diesel. The analysis of the emissions at engine exhaust highlights that hydrogenated fuel allows to reduce CO, total hydrocarbon emissions, particulate matter and NOx.

Nowadays, the push for more ecological low-carbon propulsion systems is high in all mobility sectors, including the recreational or light-commercial boating, where propulsion is usually provided by internal combustion engines derived from road applications. In this work, the effects of replacing conventional fossil-derived B7 diesel with Hydrotreated Vegetable Oil (HVO) were experimentally investigated in a modern Medium-Duty Engine, using the advanced biofuel as drop-in and testing according to the ISO 8178 marine standard. The compounded results showed significant benefits in terms of NOx, Soot, mass fuel consumption and WTW CO2 thanks to the inner properties of the aromatic-free, hydrogen-rich renewable fuel, with no impact on the engine power and minimal deterioration of the volumetric fuel economy.

Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras.

Gas bearings are an effective solution to high-speed rotor applications for its contamination free, reduced maintenance and higher reliability. However, low viscosity of gas leads to lower dynamic stiffness and damping characteristics resulting in low load carrying capacity and instability at higher speeds. Gas bearings can be enhanced by adding a foil structure commonly known as gas foil bearings (GFBs), whose dynamic stiffness can be tailored by modifying the geometry and the material properties resulting in better stability and higher load carrying capacity. A detailed study is required to assess the performance of high-speed rotor systems supported on GFBs, therefore in this study a bump type GFB is analyzed for its static and dynamic characteristics. The static characteristics are obtained by solving the non-linear Reynolds equation through an iterative procedure.

For electric vehicles, road noise, together with wind noise, is the most important contributor for vehicle interior noise. Road noise is very dependent on the NVH behavior of axle system including wheels and tires. Axle system is part of vehicle platform which should be compatible with different body variants. Therefore, il is important to characterize the NVH performance of an axle system independently of car body structure, so that the design the axle can be optimized at the early stage according to the global requirements of all the related vehicles. The best way to characterize the NVH performance of an axle system is to measure the blocked forces on an appropriate test rig. However, the measurement of blocked forces from an axle system requires very stiff boundary conditions which is difficult to achieve in practice. For axles with rigid mountings, it is nearly impossible to measure the blocked forces on test rig.

Despite being ubiquitous elements in aerospace structures, thin cylindrical shells’ catastrophic buckling response under axial compression has still remained an enigma. The recent advancements in theoretical and numerical studies aided in realising the role of localisation in shell buckling. However, the buckling being instantaneous made it unfeasible for the experimental observations to corroborate the numerical results. This necessitates high-fidelity shell buckling experiments using full-filed measurement techniques. Cut-outs are deliberate and inevitable geometrical imperfections in actual structures that could dictate the buckling response. Additive manufacturing makes it feasible to fabricate shells with tailored imperfections and study various conceivable designs.

The Selective Laser Melting (SLM) process is employed in high-precision layer-by-layer Additive Manufacturing (AM) on powder bed and aims to fabricate high-quality structural components. To gain a comprehensive understanding of the process and its optimization, both modeling and simulation in conjunction with extensive experimental studies along with laser calibration studies have been attempted. Multiscale and multi-physics-based simulations have the potential to bring out a new level of insight into the complex interaction of laser melting, solidification, and defect formation in the SLM parts. SLM process encompasses various physical phenomena during the formation of metal parts, starting with laser beam incidence and heat generation, heat transfer, melt/fluid flow, phase transition, and microstructure solidification. To effectively model this Multiphysics problem, it is imperative to consider different scales and compatible boundary conditions in the simulations.

The paper presents a theoretical framework for the detection and first-level preliminary identification of potential defects on aero-structure components while employing ultrasonic guided wave based structural health monitoring strategies, systems and tools. In particular, we focus our study on ground inspection using laser-Doppler scan of surface velocity field, which can also be partly reconstructed or monitored using point sensors and actuators on-board structurally integrated. Using direct wave field data, we first question the detectability of potential defects of unknown location, size, and detailed features. Defects could be manufacturing defects or variations, which may be acceptable from design and qualification standpoint; however, those may cause significant background signal artifacts in differentiating structure progressive damage or sudden failure like impact-induced damage and fracture.

Dimensional optimization has always been a time consuming process, especially for aerodynamic bodies, requiring much tuning of dimensions and testing for each sample. Aerodynamic auxiliaries, especially wings, are design dependent on the primary model attached, as they influence the amount of lift or reduction in drag which is beneficial to the model. In this study CFD analysis is performed to obtain pressure counter of wings. For a wing, the angle of attack is essential in creating proper splits to incoming winds, even under high velocities with larger distances from the separation point. In the case of a group of wings, each wing is then mentioned as a wing element, and each wing is strategically positioned behind the previous wing in terms of its vertical height and its self-angle of attack to create maximum lift. At the same time, its drag remains variable to its shape ultimately maximizing the C L /C D ratio.

Bio-composites have gained significant attention within the aerospace industry due to their potential as a sustainable solution that addresses the demand for lightweight materials with reduced environmental impact. These materials blend natural fibers sourced from renewable origins, such as plant-based fibers, with polymer matrices to fabricate composite materials that exhibit desirable mechanical properties and environmental friendliness. The aerospace sector's growing interest in bio-composites originates from those composites’ capacity to mitigate the industry's carbon footprint and decrease dependence on finite resources. This study aims to investigate the suitability of utilizing plant derived flax fabric/PLA (polylactic acid) matrix-based bio-composites in aerospace applications, as well as the recyclability potential of these composites in the circular manufacturing economy.

Thermo-mechanical fatigue and natural aging due to environmental conditions are difficult to simulate in an actual test with the advanced fiber-reinforced composites, where their fatigue and aging behavior is little understood. Predictive modeling of these processes is challenging. Thermal cyclic tests take a prohibitively long time, although the strain rate effect can be scaled well for accelerating the mechanical stress cycles. Glass fabric composites have important applications in aircraft and spacecraft structures including microwave transparent structures, impact-resistant parts of wing, fuselage deck and many other load bearing structures. Often additional additively manufactured features and coating on glass fabric composites are employed for thermal and anti-corrosion insulations. In this paper we employ a thermo-mechanical fatigue model based accelerated fatigue test and life prediction under hot to cold cycles.